Experiments DB Dev
bb5e2d88c0
Add variation_power.m (self-contained Monte-Carlo power for the paper's stim x day interaction, using each folder's own data as ground truth; scores per-animal cluster-honest power + LME power across N=[3..24] and effect multipliers 1/0.5) and make_variation_power.m, which drops powersim.m into every variations/<name>/ folder and runs it, writing power_result.txt beside the existing data.csv/analyze.m/result.txt. Named powersim (not power) to avoid shadowing the MATLAB builtin. All 28 folders processed. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
30 lines
1.0 KiB
Matlab
30 lines
1.0 KiB
Matlab
function make_variation_power()
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%MAKE_VARIATION_POWER Add a power-simulation script + result to every variation.
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% MAKE_VARIATION_POWER() copies variation_power.m into each
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% variations/<name>/ folder that contains a data.csv (as powersim.m) and runs
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% it, producing power_result.txt beside the existing data.csv / analyze.m /
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% result.txt. Re-runnable; also picks up any folders added later.
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thisDir = fileparts(mfilename('fullpath'));
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template = fullfile(thisDir, 'variation_power.m');
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root = fullfile(thisDir, 'variations');
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d = dir(root);
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n = 0;
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for i = 1:numel(d)
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if ~d(i).isdir || ismember(d(i).name, {'.', '..'}); continue; end
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folder = fullfile(root, d(i).name);
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if ~exist(fullfile(folder, 'data.csv'), 'file'); continue; end
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copyfile(template, fullfile(folder, 'powersim.m'));
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fprintf('\n### %s ###\n', d(i).name);
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localRun(fullfile(folder, 'powersim.m'));
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n = n + 1;
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end
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fprintf('\nAdded powersim.m + power_result.txt to %d variation folders.\n', n);
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end
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function localRun(scriptPath)
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run(scriptPath);
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end
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